class_docstr: Exponential [1] objective function.
  
  This class defines the Exponential global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Exponential}}(x) = -e^{-0.5 \sum_{i=1}^n x_i^2}
  
  
  Here, :math:`n` represents the number of dimensions and :math:`x_i \in
  [-1, 1]` for :math:`i = 1, ..., n`.
  
  *Global optimum*: :math:`f(x_i) = -1` for :math:`x_i = 0` for
  :math:`i = 1, ..., n`
  
  .. [1] Jamil, M. & Yang, X.-S. A Literature Survey of Benchmark Functions
  For Global Optimization Problems Int. Journal of Mathematical Modelling
  and Numerical Optimisation, 2013, 4, 150-194.
  
  TODO Jamil are missing a minus sign on fglob
code: def fun(self, x, *args):
      self.nfev += 1
  
      return -exp(-0.5 * sum(x**2.0))
  
imports: from numpy import abs, asarray, cos, exp, arange, pi, sin, sqrt, sum
  from .go_benchmark import Benchmark
label_desc: Use image node_id 2 for calling the Exponential obj's underlying member method code with example usage: obj.fun(x) and returns: unknown